Abolish! Against the Use of Risk Assessment Algorithms at Sentencing in the US Criminal Justice System

Philosophy and Technology 34 (4):1883-1904 (2021)
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Abstract

In this article, I show why it is necessary to abolish the use of predictive algorithms in the US criminal justice system at sentencing. After presenting the functioning of these algorithms in their context of emergence, I offer three arguments to demonstrate why their abolition is imperative. First, I show that sentencing based on predictive algorithms induces a process of rewriting the temporality of the judged individual, flattening their life into a present inescapably doomed by its past. Second, I demonstrate that recursive processes, comprising predictive algorithms and the decisions based on their predictions, systematically suppress outliers and progressively transform reality to match predictions. In my third and final argument, I show that decisions made on the basis of predictive algorithms actively perform a biopolitical understanding of justice as management and modulation of risks. In such a framework, justice becomes a means to maintain a perverse social homeostasis that systematically exposes disenfranchised Black and Brown populations to risk.

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Katia Schwerzmann
Kulturwissenschaftliches Institute, Essen, Germany

References found in this work

How to do things with words.John L. Austin - 1962 - Oxford [Eng.]: Clarendon Press. Edited by Marina Sbisá & J. O. Urmson.
Democratizing Algorithmic Fairness.Pak-Hang Wong - 2020 - Philosophy and Technology 33 (2):225-244.

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